Age and gender classification from facial features and object detection with machine learning
- سال انتشار: 1401
- محل انتشار: نشریه گسترش مجموعه فازی و کاربردهای آن، دوره: 3، شماره: 3
- کد COI اختصاصی: JR_JFEA-3-3_004
- زبان مقاله: انگلیسی
- تعداد مشاهده: 330
نویسندگان
Department of Electrical and Electronics Engineering, TOBB University of Economics and Technology, Ankara, Turkey.
Department of Electrical and Electronics Engineering, TOBB University of Economics and Technology, Ankara, Turkey.
Department of Electrical and Electronics Engineering, TOBB University of Economics and Technology, Ankara, Turkey.
Department of Electrical and Electronics Engineering, TOBB University of Economics and Technology, Ankara, Turkey.
Department of Electrical and Electronics Engineering, TOBB University of Economics and Technology, Ankara, Turkey.
چکیده
In recent years, development of the machine learning algorithms has led to the creation of intelligent surveillance systems. Thanks to the machine learning, it is possible to perform intelligent surveillance by recognizing people's facial features, classifying their age and gender, and detecting objects around instead of ordinary surveillance. In this study, a novel algorithm has been developed that classifies people's age and gender with a high accuracy rate. In addition, a novel object recognition algorithm has been developed that detects objects quickly and with high accuracy. In this study, age and gender classification was made based on the facial features of people using Convolutional Neural Network (CNN) architecture. Secondly, object detection was performed using different machine learning algorithms and the performance of the different machine learning algorithms was compared in terms of median average precision and inference time. The accuracy of the age and gender classification algorithm was tested using the Adience dataset and the results were graphed. The experimental results show that age and gender classification algorithms successfully classify people's age and gender. Then, the performances of object detection algorithms were tested using the COCO dataset and the results were presented in graphics. The experimental results stress that machine learning algorithms can successfully detect objects.کلیدواژه ها
Face Detection, Facial feature extraction, convolutional neural network, Gender classification, Age classification, Machine Learning, object detectionاطلاعات بیشتر در مورد COI
COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.
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